Quantitative accuracy of virtual non-contrast images derived from spectral detector computed tomography: an abdominal phantom study

基于光谱探测器计算机断层扫描的虚拟非对比图像的定量精度:腹部模型研究

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Abstract

Dual-energy CT allows for the reconstruction of virtual non-contrast (VNC) images. VNC images have the potential to replace true non-contrast scans in various clinical applications. This study investigated the quantitative accuracy of VNC attenuation images considering different parameters for acquisition and reconstruction. An abdomen phantom with 7 different tissue types (different combinations of 3 base materials and 5 iodine concentrations) was scanned using a spectral detector CT (SDCT). Different phantom sizes (S, M, L), volume computed tomography dose indices (CTDIvol 10, 15, 20 mGy), kernel settings (soft, standard, sharp), and denoising levels (low, medium, high) were tested. Conventional and VNC images were reconstructed and analyzed based on regions of interest (ROI). Mean and standard deviation were recorded and differences in attenuation between corresponding base materials and VNC was calculated (VNCerror). Statistic analysis included ANOVA, Wilcoxon test and multivariate regression analysis. Overall, the VNC(error) was - 1.4 ± 6.1 HU. While radiation dose, kernel setting, and denoising level did not influence VNC(error) significantly, phantom size, iodine content and base material had a significant effect (e.g. S vs. M: - 1.2 ± 4.9 HU vs. - 2.1 ± 6.0 HU; 0.0 mg/ml vs. 5.0 mg/ml: - 4.0 ± 3.5 HU vs. 5.1 ± 5.0 HU and 35-HU-base vs. 54-HU-base: - 3.5 ± 4.4 HU vs. 0.7 ± 6.5; all p ≤ 0.05). The overall accuracy of VNC images from SDCT is high and independent from dose, kernel, and denoising settings; however, shows a dependency on patient size, base material, and iodine content; particularly the latter results in small, yet, noticeable differences in VNC attenuation.

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